A new benchmark based on recent advances in multispectral pansharpening: Revisiting pansharpening with classical and emerging pansharpening methods
Pansharpening refers to the fusion of a multispectral (MS) image and panchromatic (PAN)
data aimed at generating an outcome with the same spatial resolution of the PAN data and …
data aimed at generating an outcome with the same spatial resolution of the PAN data and …
Machine learning in pansharpening: A benchmark, from shallow to deep networks
Machine learning (ML) is influencing the literature in several research fields, often through
state-of-the-art approaches. In the past several years, ML has been explored for …
state-of-the-art approaches. In the past several years, ML has been explored for …
Target-adaptive CNN-based pansharpening
We recently proposed a convolutional neural network (CNN) for remote sensing image
pansharpening obtaining a significant performance gain over the state of the art. In this …
pansharpening obtaining a significant performance gain over the state of the art. In this …
A benchmarking protocol for pansharpening: Dataset, preprocessing, and quality assessment
Comparative evaluation is a requirement for reproducible science and objective assessment
of new algorithms. Reproducible research in the field of pansharpening of very high …
of new algorithms. Reproducible research in the field of pansharpening of very high …
Hyperspectral Pansharpening: Critical review, tools, and future perspectives
Hyperspectral (HS) pansharpening consists of fusing a high-resolution panchromatic (PAN)
band and a low-resolution HS image to obtain a new image with high resolution in both the …
band and a low-resolution HS image to obtain a new image with high resolution in both the …
Diffusion model with disentangled modulations for sharpening multispectral and hyperspectral images
The denoising diffusion model has received increasing attention in the field of image
generation in recent years, thanks to its powerful generation capability. However, diffusion …
generation in recent years, thanks to its powerful generation capability. However, diffusion …
Full-resolution quality assessment of pansharpening: Theoretical and hands-on approaches
Panchromatic (Pan) sharpening, or pansharpening, refers to the combination of a
multispectral (MS) image and Pan data with a finer spatial resolution. Since the early days of …
multispectral (MS) image and Pan data with a finer spatial resolution. Since the early days of …
UPanGAN: Unsupervised pansharpening based on the spectral and spatial loss constrained generative adversarial network
It is observed that, in most of the CNN-based pansharpening methods, the multispectral
(MS) images are taken as the ground truth, and the downsampled panchromatic (Pan) and …
(MS) images are taken as the ground truth, and the downsampled panchromatic (Pan) and …
Detail-injection-model-inspired deep fusion network for pansharpening
Pansharpening is an image fusion procedure, which aims to produce a high spatial
resolution multispectral (MS) image by combining a low spatial resolution MS image and a …
resolution multispectral (MS) image by combining a low spatial resolution MS image and a …
Pansharpening by convolutional neural networks in the full resolution framework
In recent years, there has been a growing interest in deep learning-based pansharpening.
Thus far, research has mainly focused on architectures. Nonetheless, model training is an …
Thus far, research has mainly focused on architectures. Nonetheless, model training is an …